The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctch...
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The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctcharacteristic of batteries for eVTOLs is that the discharge rates are significantly larger during take-off andlanding, compared with the battery discharge rates needed for automotives. Such discharge protocols areexpected to impact the long-run health of batteries. This paper proposes a data-driven machine learningframework to estimate the state-of-health and remaining-useful-lifetime of eVTOL batteries under varying flightconditions and taking into account the entire flight profile of the eVTOLs. Three main features are consideredfor the assessment of the health of the batteries: charge, discharge and temperature. The importance of thesefeatures is also quantified. Considering battery charging before flight, a selection of missions for state-ofhealth and remaining-useful-lifetime prediction is performed. The results show that indeed, discharge-relatedfeatures have the highest importance when predicting battery state-of-health and *** several machine learning algorithms, it is shown that the battery state-of-health and remaining-useful-lifeare well estimated using Random Forest regression and Extreme Gradient Boosting, respectively.
Amidst growing global concerns over climate change and escalating greenhouse gas emissions from fossil fuels, the pursuit of renewable energy sources has become critical. This study focuses on harnessing hydropower us...
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This paper focuses on the impact of out-of-school and in-school use of digital technologies on the reading and information literacy skills of 15-year-old Slovenian students who participated in the PISA 2018 study. For...
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This paper develops an implementation of a measurement and control system in which a vehicle follows its predecessor while maintaining a certain distance. First, we construct a model that virtually delays the referenc...
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The focusofourwork is on themost recent results infixedpoint theoryrelated *** variants of(s,q,φ,F)-contractions that expand,supplement and unify an important work widely discussed in the literature,based on existing...
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The focusofourwork is on themost recent results infixedpoint theoryrelated *** variants of(s,q,φ,F)-contractions that expand,supplement and unify an important work widely discussed in the literature,based on existing classes of interpolative and *** particular,a large class of contractions in terms of s,q,φand F for both linear and nonlinear contractions are defined in the framework of b-metric-like *** main result in our paper is that(s,q,φ,F)-g-weak contractions have a fixed point in b-metric-like spaces if function F or the specified contraction is *** an application of our results,we have shown the existence and uniqueness of solutions of some classes of nonlinear integral equations.
One of the significant opportunities for reducing energy waste and carbon emissions is the renovation, modernization, and rehabilitation of existing buildings. Replacing the windows of existing residential buildings w...
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This study delves into the significant role played by Quantum Dot Semiconductor Optical Amplifiers (QD-SOAs) in meeting the ever-growing bandwidth demands. QD-SOAs offer a unique blend of cost-effectiveness, integrati...
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In industrial inspection, the detection of surface defects - such as scratches, dents, or other defects - is crucial for ensuring product quality. However, the limited availability of annotated images of such defects ...
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Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language *** modeling,crucial for AI development,has evolved from statistical to neural models over the last two ***,trans...
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Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language *** modeling,crucial for AI development,has evolved from statistical to neural models over the last two ***,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training *** the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models *** advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal *** survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language ***,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI ***,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.
This paper deals with the exploration of a system which acts on demand in case of emergency matter. To verify functionality, each component of the system must be regularly inspected with a specified inspection interva...
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